class_docstr: h2oGPT Client.
docstr: Creates a GPT client.
  :param src: either the full URL to the hosted h2oGPT
      (e.g. "http://0.0.0.0:7860", "https://fc752f297207f01c32.gradio.live")
      or name of the Hugging Face Space to load, (e.g. "h2oai/h2ogpt-chatbot")
  :param h2ogpt_key: access key to connect with a h2oGPT server
  :param huggingface_token: Hugging Face token to use to access private Spaces
docstr_tok: ["Creates","a","GPT","client",".",":","param","src",":","either","the","full","URL","to","the","hosted","h2oGPT","(","e.g",".","``","http",":","\/\/0.0.0.0:7860","''",",","``","https",":","\/\/fc752f297207f01c32.gradio.live","''",")","or","name","of","the","Hugging","Face","Space","to","load",",","(","e.g",".","``","h2oai\/h2ogpt-chatbot","''",")",":","param","h2ogpt_key",":","access","key","to","connect","with","a","h2oGPT","server",":","param","huggingface_token",":","Hugging","Face","token","to","use","to","access","private","Spaces"]
code: def __init__(
      self,
      src: str,
      h2ogpt_key: Optional[str] = None,
      huggingface_token: Optional[str] = None,
  ):
      """
      Creates a GPT client.
      :param src: either the full URL to the hosted h2oGPT
          (e.g. "http://0.0.0.0:7860", "https://fc752f297207f01c32.gradio.live")
          or name of the Hugging Face Space to load, (e.g. "h2oai/h2ogpt-chatbot")
      :param h2ogpt_key: access key to connect with a h2oGPT server
      :param huggingface_token: Hugging Face token to use to access private Spaces
      """
      self._client = GradioClientWrapper(
          src, h2ogpt_key, huggingface_token
      )
      self._text_completion = TextCompletionCreator(self._client)
      self._chat_completion = ChatCompletionCreator(self._client)
      self._models = Models(self._client)
      self._server = Server(self._client)
  
file_path: h2ogpt/client/h2ogpt_client/_core.py
imports: from typing import Optional
  from h2ogpt_client._completion import ChatCompletionCreator, TextCompletionCreator
  from h2ogpt_client._gradio_client import GradioClientWrapper
  from h2ogpt_client._models import Models
  from h2ogpt_client._server import Server
label_desc: Use image node_id 1 to create a new Client object  with example: obj = Client(src, h2ogpt_key, huggingface_token)